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Dana Pe'er and Nir Hacohen. Principles and strategies for developing network models in cancer. Cell 2011, 144: 864-872.
准则1:分子间相互影响产生数据中的统计相关性(Molecular influences generate statistical relations in data)
准则2:网络不是一成不变的:上下文相关与动态性(Networks are not fixed: the role of context and dynamics)
准则3:找到“差异”网络(Extracting "differential" networks)
策略1:发现遗传位点和体突变(Discovery of inherited alleles and somatic mutations)
策略2:用RNAi发现网络关键部分(Discovering key network components using RNAi)
策略3:统计识别异常调控的基因及其调控因子(Statistical identification of dysregulated genes and their regulators)
策略4:整合基因型和基因表达数据为因果模型(Integrating genotype and gene expression into causal models)
策略5:整合单细胞数据来解决细胞间的遗传异质性(Integration of single cell data to account for cell-cell heterogeneity)
策略6:用扰动来发现网络重构(Using perturbations to reveal network wiring)
未来前景:个性化肿瘤医疗(Personalized cancer medicine)
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